Are you a talented Data Engineer looking to join a scaling startup? Do you enjoy being part of a team that makes a real difference to the success of small business owners? If you are ready to help evolve and scale the data infrastructure that empowers entrepreneurs, read on.
Overview:
FundThrough is looking for a Data Engineer to not only build data pipelines but also extend the next generation of our data tools. As a Data Engineer, you will develop a clear sense of connection and purpose with our organization and leadership; Data Engineering is the eyes through which we see our product’s success and opportunities. As a member of the Data Science & Engineering team you will contribute to a variety of projects and technologies that include microservices, event-driven design, analytics, ML modeling, tooling, services, and more.
The ideal candidate is self-motivated, highly collaborative, someone who thrives in a fast paced environment, and gets excited to work with the latest stack of technologies on rapidly growing products.
About the company:
FundThrough is a leading fintech company accelerating cash flow and enabling growth for small and medium-sized businesses. Based in Toronto and operating across North America, FundThrough’s AI-powered invoice funding platform gives B2B businesses fast, customized funding offers to get their invoices paid in a few days, rather than a few months.
What you will do:
- Collaborative Architecture: Partner with the team to provide architectural suggestions and formal proposals for our core data systems. You will help ensure a seamless flow between microservices, our data lake, and downstream analytics.
- Modern Pipeline Development: Build and ship production-level data pipelines using PySpark and SQL. You will collaborate on establishing standards for idempotency, monitoring, and performance tuning.
- Lakehouse Data Modeling: Implement robust data modeling patterns (Medallion architecture: Bronze/Silver/Gold). You will ensure our Lakehouse is not just a data dump, but a high-performance source of truth for both BI and ML.
- Databricks & Lakehouse Evolution: Contribute to the continuous improvement of our Databricks environment, with a focus on Delta Lake optimization and robust governance via Unity Catalog.
- Systems Evolution & Stability: Act as the steward of our production environment. You will lead the refactoring of legacy pipelines to improve observability, reduce technical debt, and ensure seamless data flow between our microservices and the Databricks Lakehouse.
- Technical Influence: Work closely with the Director of Data to refine our technical roadmap. You will lead by example through deep-dive code reviews and by maintaining a high bar for technical documentation.
- Reliability & Governance: Conduct comprehensive audits to identify system inefficiencies. You will share ownership of data quality, security, and privacy across the entire lifecycle of our datasets.
Requirements
- Experience: 2 - 4+ years of hands-on data engineering experience, ideally within a high-growth SaaS or Fintech environment.
- Tooling Expertise: Strong fundamental knowledge of the Databricks ecosystem (Spark, Delta Lake, Workflows) and AWS cloud infrastructure. Proficient experience with Apache Airflow for workflow management.
- Technical Mastery: High proficiency in Python/PySpark and SQL. You should have a clear philosophy on what makes code maintainable and scalable.
- AI/ML Literacy: Practical experience or a deep interest in the data requirements for GenAI, including handling data for LLMs and vector databases.
- Platform Mindset: Experience with Infrastructure-as-Code (Terraform/CDK) and a strong commitment to CI/CD and automated testing.
- Communication: "Strong opinions, loosely held." You can navigate complex technical trade-offs and communicate architectural proposals clearly to stakeholders at all levels.
Bonus Points
- Experience with Event-Driven Architectures (Kafka or Spark Structured Streaming).
- Familiarity with dbt (data build tool) for modular data modeling.
- Hands-on experience with Databricks Mosaic AI or model serving.
- Experience querying and optimizing large datasets using Presto, Hive, or similar engines.
Benefits
- Opportunity to leave your mark on a growing startup
- An incredibly diverse team of brilliant minds from all over the world
- Competitive compensation
- Family-friendly policies
- Work from home
- Birthday treats, and a lunch of your choice every week (one of our values is Fun & Food!)
Open and honest is one of our core values at FundThrough and in this spirit, we are sharing we do not use AI tools in our hiring process and kindly request that applicants refrain from using AI during the interview process.
Please note that due to the sensitive nature of the work we do, clearing a criminal record check is a condition of employment. FundThrough encourages applications from candidates with differing abilities. Please let us know if you require accommodation at any stage in the selection process.
**PLEASE SUBMIT YOUR RESUME AND COVER LETTER IN ENGLISH**